Protective Effects of Protegrin in Dextran Sodium Sulfate-Induced Murine Colitis
Bibliographic record
Abstract
Cathelicidins, a class of antimicrobial peptides, have been widely studied for their antimicrobial role in innate immune responses during infection and inflammation. At sub-antimicrobial concentrations, various cathelicidins from different species have been reported to exert chemotactic activity on neutrophils, monocytes, dendritic cells and T-cells, and also enhance angiogenesis and wound healing. To date, the role of the pig cathelicidin, protegrin-1 (PG-1), in immune modulation and tissue repair in the intestinal tract has not been investigated. The aim of the present study was to examine the potential protective effects of recombinant PG-1 in a mouse dextran sulfate sodium (DSS)-induced colitis inflammation model. This is the first report showing the protective effects of PG-1 in its various forms (pro-, cathelin-, and mature- form) in attenuating significant body weight loss associated with DSS-induced colitis (p<0.05). PG-1 treatment improved histological scores (P<0.05) and influenced the gene expression of inflammatory mediators and tissue repair factors such as trefoil factor (TFF3) and mucin (MUC-2). Protegrin treatment also altered the metabolite profile, returning the metabolite levels back closer to untreated control levels. These findings lay the foundation for future oral application of recombinant PG-1 to potentially treat intestinal damage and inflammation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".